Chronic alcohol exposure causes widespread changes in CNS molecular function impacting brain function and behavior, contributing to alcohol dependence and pathology. Due to the nature of the alcohol withdrawal and the emotional and physical consequences, the central nucleus of the amygdala (CeA) is an area of significant interest. Recently published and preliminary data suggest that these molecular processes accommodate to chronic alcohol exposure over time. However these same molecular processes respond quickly to abrupt changes in alcohol exposure as reflected in significant changes in gene expression in whole tissue punches of the CeA. These changes progress over a long period of time during alcohol withdrawal. Moreover, preliminary data supports our hypothesis that neurons of a phenotypic brain nucleus are adaptive in response to changed inputs. These varied inputs result in the formation of distinct functional states within a cell-phenotype. Taken in context, we note that the CeA neurons integrate a variety of synaptic inputs and signals from sources including catecholaminergic afferents, pontine-visceral inputs, and the hypothalamus. Therefore it is likely that individual CeA neurons respond to varied and combinatorial inputs resulting in differentiated functional states. These distinct functional state subsequently result in differentiated neuronal contributions to the evolving state of the CeA during withdrawal. Thus, understanding the molecular framework of these distinct functional states will help reveal mechanisms subtending the response of the CeA. To this end, I will characterize the responses of neurons within the CeA at the molecular level under various stages of alcohol dependence and withdrawal. I propose to develop gene regulatory network models that will help characterize the functional gene relationships governing the adaptive response of individual neurons. The result will be refined network models that will describe the complex functional relationships underlying distinct input-driven neuronal states. Subsequently these refined networks will yield insight into how synaptic inputs drive individual neurons into differentiated states that differentially contribute to the evolving response of the CeA associated with the various stages of alcohol dependence and withdrawal.